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Information retrieval multiple choice questions with answers, IR MCQs with answers, solved information retrieval questions, information retrieval objective type questions with solutions, information retrieval exam questions

Information Retrieval Multiple Choice Questions with Answers

• Information Retrieval MCQs with Answers - SET 01

  • Keywords: precision, query expansion, classical IR models
    

• Information Retrieval MCQs with Answers - SET 02

  • Keywords: stop word removal, heaps' law, inverted index, idf
    

• Information Retrieval MCQs with Answers - SET 03

  • Keywords: Zipf's law, inverted index, IR formal definition, fallout ratio
    

• Information Retrieval MCQs with Answers - SET 04

  • Keywords: Stemming, query expansion, recall, relevance, homonym
    

• Information Retrieval MCQs with Answers - SET 05

  • Keywords: Stemming, recall, click relevance feedback, TF-IDF
    

• Information Retrieval MCQs with Answers - SET 06

• Keywords: Precision, false positive

• Information Retrieval MCQs with Answers - SET 07

• Information Retrieval MCQs with Answers - SET 08

• Information Retrieval MCQs with Answers - SET 09

• Information Retrieval MCQs with Answers - SET 10

• Information Retrieval MCQs with Answers - SET 11

• Information Retrieval MCQs with Answers - SET 12

• Information Retrieval MCQs with Answers - SET 13

• Information Retrieval MCQs with Answers - SET 14

• Information Retrieval MCQs with Answers - SET 15

 

Keywords

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List down the local methods for improving recall of IR systems

What are the local methods to improve recall in a retrieval system, relevance feedback, pseudo relevance feedback methods to improve recall, local methods for query reformulation in IR system

 

Question: List down the local methods for improving recall of IR systems   Answer: Local methods go for local on-demand analysis for a user query in order to improve recall of a retrieval system. Following are the local methods for improving recall; 1. Relevance feedback It improves the query based on user feedback on relevance of the documents in the initial set of results. Users were asked explicitly to mark the documents as relevant or non-relevant. This feedback is used to reformulate the query to produce new search results. 2. Pseudo relevance feedback Pseudo relevance feedback, also known as blind relevance feedback, provides a method for automatic local analysis. It automates the manual part of relevance feedback, so that the user gets improved retrieval performance without an extended interaction. 3. Indirect relevance feedback

 

Related links/questions

• How to improve the recall of an information retrieval system

• What are the global resources for query expansion / reformulation?

• Machine learning multiple choices questions with detailed answers - home page

• What are the problems/disadvantages with Jaccard similarity coefficient?
  

• What are the components of a benchmark data collection?

• What are the drawbacks of Boolean retrieval model?

• What are the drawbacks of relevance feedback in improving search results

• Common preprocessing steps and their significance in information retrieval

 

 

             

Keywords

Relevance feedback in information retrieval

Pseudo relevance feedback in information retrieval

Evaluation of information retrieval systems

Local methods for query reformulation

IR techniques for relevance feedback

Relevance feedback and query reformulation in IR

Query expansion techniques for information retrieval